The modern business landscape has changed significantly in recent years and, as businesses strive towards becoming more digital, the ecosystem becomes increasingly problematic from a technological perspective. On one side of the coin, you have the emerging technologies and trends that give enterprises a competitive edge within their space. On the other, we have the foundational technologies that may not garner as much attention as the former but are still critical for driving digital transformation. For this reason, data remains a business' most valuable asset and is the fuel behind delivering real digital transformation.
Business data has been around for decades, but it has become apparent that as new, emerging technologies such as artificial intelligence, internet of things and predictive analytics continue to make their mark, having access to sufficient and accurate data has never been more critical. However, the past year has been like no other and, due to the current climate, management of this data may have taken a step back with organizations failing to maintain quality information without the use of increased automation effectively.
The true cost of human error
A report by Snaplogic found that 42 percent of data management processes that could be automated are delivered manually. As a result, the report found that 93 percent of the IT decision-makers surveyed said they need to improve the way their organization collects, manages and stores their data. What's more, with many companies choosing to manage their data manually, they are also leaving themselves open to one of the biggest challenges within the IT sector - Human Error. According to research from Insurance Firm, Gallagher, 3.5 million businesses across the UK have suffered from a breach of security or cyberattacks from negligence with 60 percent claiming it down to human error.
Organizations need to understand the significance of manually managing and storing data, particularly if they hold sensitive information. As sophisticated as technology becomes, human error still equates as a significant reason for several data breaches or mishandlings. There are countless stories of IT managers backing up company information on flash drives and then misplacing them or organizations deleting critical data altogether. For example, in 2017, DevOps platform GitLab was scrutinized when they accidentally deleted client data and due to the manual backup not working, lost access to a vast amount of data. Not only did this impact the business' reputation but meant the platform was down for 18 hours and impacted more than 5,000 client projects worth billions of dollars.
The manual management of data is costing organizations a significant amount of time and money. However, what about those who have had their data exposed? In January 2020 the UK government was under scrutiny when it was revealed that betting companies were granted access to a Department of Education database that contained personal information on more than 28 million students across the UK. With regulations such as GDPR hitting organizations with significant fines for breaching their policies, it is important that institutions establish trust with those consenting to give them their data in the first place to ensure it will be protected and managed with care and vigilance.
Implementing a data strategy to make automation work for you
CTOs and CIOs already have the task of balancing driving innovation across their companies while also keeping budgets in line with CFO and CEO expectations. However, due to the current climate and the need to enable staff to work remotely, effective data management can fall by the wayside. What’s more, with the majority of the UK workforce still working from home, companies need to adapt to how they securely and effectively manage their data. With businesses holding more critical data than before, companies need to ensure they have a robust automation framework to reduce human error and data mismanagement risks.
More organizations need to take a forward-vision look toward automation tools that enable businesses to collect, store, manage and analyze quality data. Utilizing tools such as machine learning designed to carry out repetitive tasks in aggregation and curation, enterprises can remove the need, or at least reduce the time spent on manual data management. Artificial Intelligence (AI) has become increasingly sophisticated within the past few years, enabling businesses to identify data patterns; and remove duplicated and self-correct insufficient data. Yet, we are still just scratching the surface with this technology and its data management capabilities and we can expect to see it continue to evolve and establish itself as a key management tool.
Gartner predicts that automation will reduce manual Data Management tasks by 45 percent by as soon as 2022; enabling businesses to save time and money and enabling CTOs and CIOs to spend their time on business-critical tasks. However, to fully utilize automation, companies need to have a clear Data Strategy to understand how automation will benefit them. For example, some platforms are restricted to particular applications or different tools may have a specific focus on one aspect of data management; whether it be storage, backup or a device that focuses on overall data quality. Businesses first need to establish how automation will benefit their organization and where it will provide more value.
While companies need to trust more in automation, it shouldn't be a step that is taken lightly and needs considering. A poor Data Strategy could not only end in a disaster but could cost a business more time and money than manually managing their data. Therefore, an effective strategy needs to be put in place to maximize automation and ensure the company reaps the benefits, not pay for the consequences.
Data is one of the most significant resources for an organization. However, with the current climate rife with uncertainty globally, it has never been more critical for companies to protect and leverage their greatest assets. With human error playing a pivotal role in data quality and mismanagement, now is the time for businesses to implement a data strategy that utilizes the latest technologies to let automation use their data and make the most of what they have.
Simon Rolph - CEO & Founder, Such Sweet Thunder